Temp Research Assistant: Cardiovascular Fluid Mechanics

Worcester Polytechnic Institute; Maryland; On-site; USD 28,000 - 34,000; Full time

Benefits offered by this job

State-of-the-art facilities

Collaborations with hospitals

Career development

Job summary

The Artificial Intelligence and Modeling Laboratory for Cardiovascular Diseases (AIMCardio Lab) at Worcester Polytechnic Institute (WPI) seeks two temporary research assistants. We look for researchers with expertise in fluid-structure interaction, computational and experimental fluid mechanics, and/or scientific machine learning, focusing on cardiovascular diseases and medical devices.

The appointment is for one year with possible renewal based on performance and funding; successful candidates

Qualifications

• BS or MS in Mechanical Engineering, Biomedical Engineering, Aerospace Engineering, Electrical Engineering, Applied Mathematics, Computer Science, or a closely related field.
• Experience with experimental fluid mechanics and flow visualization techniques (PIV, flow imaging) preferred.
• CFD/Multiphysics simulations and strong programming, numerical modeling skills.

Responsibilities

• Contribute to research in cardiovascular fluid mechanics and AI-driven modeling.
• Collaborate with interdisciplinary teams across clinical and engineering domains.
• Publish findings and present at seminars and conferences.

Skills

Fluid-structure interaction

Computational fluid dynamics

Multiphysics simulation

Finite element analysis

Education

BS or MS in Mechanical/Biomedical/Aerospace/ Electrical/Applied Mathematics/Computer Science or related field

Related fields considered

Tools

PIV

CFD software

Programming skills

FEA tools

Job description

The Artificial Intelligence and Modeling Laboratory for Cardiovascular Diseases (AIMCardio Lab) at Worcester Polytechnic Institute (WPI) seeks two temporary research assistants. We look for researchers with expertise in fluid-structure interaction, computational and experimental fluid mechanics, and/or scientific machine learning, focusing on cardiovascular diseases and medical devices.

The appointment is for one year with possible renewal based on performance and funding; successful candidates